Use Of PPG Research Articles

Early Detection of Cardiovascular Disease Using Photoplethysmography (PPG) Signal Analysis

Photoplethysmography (PPG) signals have gained prominence in clinical diagnostics for their non-invasive, cost-effective, and user-friendly applications in detecting cardiovascular diseases (CVDs). This study leverages machine learning techniques to enhance the accuracy of CVD detection from PPG data, addressing critical risk factors such as hypertension and stress, which significantly contribute to elevated blood pressure and, consequently, to cardiovascular disorders. The use of PPG provides a reliable approach for identifying cardiovascular anomalies by monitoring essential parameters like blood pressure and heart rate. In this work, we employ both machine learning and deep learning, specifically neural networks, to assist clinicians in diagnosing CVD, achieving a high accuracy rate of 98% on the PPG-BP dataset. The findings demonstrate the potential of PPG signals combined with advanced algorithms to support early diagnosis and personalized treatment, ultimately reducing mortality rates associated with cardiovascular diseases.

Epidemiological Relationship of Photoplethysmography Signal Derived from Arterial Stiffness and Blood Pressure to Coronary Artery Disease: A Systematic Review

Current photoplethysmography (PPG) signals and electronic devices had a lot of attention including analysis of coronary heart disease, ageing of blood vessels, metabolic syndrome, endothelial cell damage, predicting the risk of coronary artery disease, and community-acquired pneumonia. This systematic review aims to analyze current technologies used to measure PPG signals. Analysis of PPG signals with patients involved in coronary artery disease and arterial stiffness and other important interests toward the future trends of computational medicine. The hypothesis is that arterial stiffness is epidemiologically related to the risk of coronary heart disease. A systematic search was conducted in different databases to acquire literature examining the use of PPG with coronary artery disease in terms of epidemiological correlations. Search terms included arterial stiffness, epidemiology, PPG, blood pressure, and coronary artery disease. Articles that do not measure PPG signals on real patients/subjects were excluded from the analysis. A total of 17 studies met the inclusion criteria for this systematic review. Nearly half of the studies used PPG with artificial intelligence/machine learning for analytical study patients, while 18% were PPG studies related to endothelial damage and blood pressure profiles, and another 18% were new development of PPG measurement devices. The rest was PPG analyzing coronary artery disease and atherosclerosis. Systematic review findings reveal PPG applications range from the epidemiology of damaged endothelial cell proliferation to advanced digital PPG analysis. Managing cardiovascular risk and exploring new areas including chronic kidney disease and ovarian cancer must be of interest and considered in future studies.

PPG Signal and application in the medical field

The ascent of remote health examination is a burgeoning trend in healthcare, aimed at tackling the challenge of hospital overload and streamlining the process of patient monitoring. To achieve these laudable goals, a device that is both efficient and capable of extracting critical health indicators is of paramount importance. Enter photoplethysmography (PPG) technology - a compact and user-friendly device that offers a wealth of health-related information. PPG is an optical, non-invasive method of measuring changes in blood volume in tissue by illuminating the skin and detecting variations in light absorption caused by blood flow. This technique has a multitude of applications, including the measurement of blood oxygen saturation, the estimation of blood pressure, the assessment of vascular aging, and the detection of arrhythmias. Therefore, it presents a promising avenue in addressing the challenge of hospital overload. This article provides an all-encompassing overview of photoplethysmography (PPG) technology, elucidating the underlying principles and highlighting its noteworthy applications. Specifically, the article expounds on the use of PPG in measuring blood oxygen saturation, estimating blood pressure, assessing vascular aging, and detecting arrhythmias. Despite the advantageous applications of PPG, there are still some issues that need to be addressed, such as the limited availability of PPG data sets in certain populations, the sensitivity of PPG signal to motion and ambient conditions, and a lack of clarity about the nature of PPG which leads to the absence of standard criteria in sampling and interpretation of PPG in its applications. And these issues are also thoroughly discussed in the paper.

A Study of Feature Selection Method to Detect Coronary Heart Disease (CHD) on Photoplethysmography (PPG) Signals

Coronary Heart Disease (CHD) is a condition in which the heart's blood supply is blocked or disrupted by fat in the coronary arteries. This disease is the most significant cause of death in Indonesia. CHD can be detected based on the Heart Rate Variability (HRV) index of the Photophletysmograph (PPG) signal taken from a smartphone's camera. However, the use of PPG from smartphone to detect CHD is still rare in real-world applications. Moreover, studies on CHD detection based on PPG signal are also difficult to be found in the scientific literature. Currently, the Electrocardiogram (ECG) signal still dominates as a signal for detecting CHD. This research fills this research gap by proposing a study on the feature selection of PPG signal to detect CHD. There are three feature selection methods studied in this research, i.e., Analysis of Variance (Anova), Pearson Correlation, and Recursive Feature Elimination (RFE). Furthermore, a classification algorithm, called as K-Nearest Neighbors, has also been chosen to create a machine learning model based on the PPG features. The experimental results show that the Pearson Correlation feature selection method produces better CHD detection performance compared to the other two algorithms (Anova and RFE). CHD detection performance using the Pearson Correlation produces an accuracy of 90.9%, sensitivity of 75%, and specificity of 100%.

Preprocessing and Mathematical Analysis of PPG Signals

The report presents the main research trends in the preprocessing and mathematical analysis of photoplethysmographic signals. The use of PPG in recent years has grown in parallel with the deepening penetration of modern technology in people's daily lives. At the same time, the modernization of technology has led to the miniaturization of optical sensors. A detailed overview of the state of PPG technology today and the possibilities of using PPG sensors for reporting and long-term monitoring of the health of people in their daily lives is offered. The report considers methods for noise reduction in photoplethysmographic signals based on the use of discrete wavelet transform and threshold processing of the obtained coefficients. A comparison is made between the presented methods on the basis of evaluation parameters.

The Relevance of Calibration in Machine Learning-Based Hypertension Risk Assessment Combining Photoplethysmography and Electrocardiography.

The detection of hypertension (HT) is of great importance for the early diagnosis of cardiovascular diseases (CVDs), as subjects with high blood pressure (BP) are asymptomatic until advanced stages of the disease. The present study proposes a classification model to discriminate between normotensive (NTS) and hypertensive (HTS) subjects employing electrocardiographic (ECG) and photoplethysmographic (PPG) recordings as an alternative to traditional cuff-based methods. A total of 913 ECG, PPG and BP recordings from 69 subjects were analyzed. Then, signal preprocessing, fiducial points extraction and feature selection were performed, providing 17 discriminatory features, such as pulse arrival and transit times, that fed machine-learning-based classifiers. The main innovation proposed in this research uncovers the relevance of previous calibration to obtain accurate HT risk assessment. This aspect has been assessed using both close and distant time test measurements with respect to calibration. The k-nearest neighbors-classifier provided the best outcomes with an accuracy for new subjects before calibration of 51.48%. The inclusion of just one calibration measurement into the model improved classification accuracy by 30%, reaching gradually more than 96% with more than six calibration measurements. Accuracy decreased with distance to calibration, but remained outstanding even days after calibration. Thus, the use of PPG and ECG recordings combined with previous subject calibration can significantly improve discrimination between NTS and HTS individuals. This strategy could be implemented in wearable devices for HT risk assessment as well as to prevent CVDs.

Cardiodiagnostics Based on Photoplethysmographic Signals.

The article presents a methodology to support the process of correct cardiodiagnostics based on cardio signals recorded with modern optical photoplethysmographic (PPG) sensor devices. An algorithm for preprocessing registered PPG signals and the formation of a time series for the analysis of heart rate variability is presented, which is an important information indicator in the diagnosis of cardiovascular diseases. In order to validate the proposed algorithm, an experimental scheme for synchronous recordings of PPG and electrocardiographic (ECG) signals and the study of the accuracy of the registered signals was created. The obtained results show high accuracy of the studied signals in terms of the following parameters: number of QRS complexes/pulse waves and mean RR intervals/PP intervals and the finding that the proposed algorithm is suitable for preprocessing PPG signals, as well as the possibility of interchangeable use of PPG and ECG. The results of the mathematical analysis of heart rate variability by applying linear methods (Time-Domain and Frequency-Domain) to two groups of people are presented: healthy controls and patients with cardiovascular disease (syncope). After determining the values of the parameters of the methods used, in order to distinguish healthy subjects from sick ones, statistical analysis was applied using t-test and Receiver Operating Characteristics (ROC) analysis. The obtained results show that the linear methods used are suitable for analysing the dynamics of PP interval series and for distinguishing healthy subjects from those with pathological diseases. The presented research and analyses can find applications in guaranteeing correctness and accuracy of conducting cardiodiagnostics in clinical practice.

Assessment of heart rate agreement on continuous photoplethysmography monitoring using a smartwatch versus beat-to-beat synchronized ECG monitoring

Abstract Background In the awakening era of mobile health, wearables equipped with photoplethysmography (PPG) technology to monitor the heart rate (HR) and rhythm are on the rise. Smartwatches and wristbands enable HR monitoring for consumers at massive scale. Unfortunately, once consumers become patients, physicians are limited by insufficient evidence to support the clinical use of PPG based wearables. Accurate identification of heartbeats is the first step in the interpretation of PPG traces and should be validated. Purpose To assess the agreement between continuous PPG monitoring using a smartwatch and continuous ECG Holter monitoring in the identification of heartbeats and calculation of the HR. Methods One hundred patients (≥18 years) without a pacemaker-dependent heart rhythm who were referred to a university hospital and a large tertiary hospital for elective 24-hour ECG Holter monitoring were asked to wear a continuous PPG monitoring smartwatch (i.e. Samsung GWA2 or Empatica E4) simultaneously with the 24-hour Holter monitor. All activities of daily life were allowed. The ECG trace and PPG waveform were synchronised and fragmented in one-minute fragments. The one-minute ECG fragments were labelled as AF, non-AF, or insufficient quality based on the routine clinical interpretation (i.e. software + physician overreading), and the average HR during each fragment was calculated by Holter algorithm. The PPG fragments were analysed by an artificial intelligence (AI) algorithm (i.e. FibriCheck) that labelled fragments as sufficient or insufficient quality, identified the number of heartbeats and calculated the HR. The agreement between the HR on ECG and PPG in sufficient quality tracings was analysed with linear regression, Pearson's product-moment correlation and Bland-Altman analysis. A subanalysis was performed for AF rhythm and non-AF rhythms. Results A total of 72,725 simultaneous ECG and PPG one-minute fragments were recorded in 96 patients, after excluding 4 patients (due to 3 Holter and 1 smartwatch technical error) and 42,520 minutes (36.9%) of insufficient quality (ECG 1,454 (1.3%); PPG 25,704 (22.3%), ECG and PPG 15,362 (13.3%)). The correlation (r=0.935) between ECG and PPG HR was statistically significant (CI 0.934–0.936; P<0.001), with a mean difference between ECG and PPG of 0.8bpm. The lower and upper limit boundary (LLB and ULB; defined as ±1.96 SD) were −8.0bpm and 9.7bpm, respectively, i.e. 95% of PPG measurements identified the HR within 8bpm below or 10bpm above the ECG reference. The mean difference between ECG and PPG HR in the AF subgroup (n=10,255 (14.1%)) was 0.9bpm (LLB −8.4bpm; ULB 10.2bpm) and 0.8bpm in the non-AF subgroup (LLB −0.8bpm; ULB 9.6bpm). Conclusion The AI algorithm analysing continuous out-of-hospital PPG tracings can annotate heartbeats and assess HR without a clinically significant bias compared to continuous ECG monitoring, both during AF and non-AF rhythms in a heterogenous patient population. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Research Foundation-Flanders, Strategic Basic Research Fund Correlation plot & Bland-Altman plot

Photoplethysmographic characteristics of the efficiency of the calf muscle-venous pump in norm and in patients with cvd of various clinical classes according to CEAP

Introduction. A literature review on the use of plethysmographic methods for studying the features of venous blood flow in lower extremities under physiological conditions and for global assessment of venous hemodynamics in chronic venous diseases urges to conduct further studies.The aim of the study was to carrying off a detailed statistical analysis of the value of the refilling time (RT) obtained during a photoplethysmographic study (PPG) to evaluate the degree of effectiveness of the calf muscle-venous pump in normal and in patients of different clinical classes according to CEAR.Materials and methods. For the period from 2002 to 2012, 116 healthy individuals with no symptoms of chronic venous diseases and 530 patients with CVD were examined with the use of PPG, with their distribution in accordance with the CEAR international classification as follows: C0-C1 – 140 people (26.42%), C2-C3 – 218 people (41.13%) and 172 persons (32.45%) had trophic disorders, that is, they belonged to the C4-C6 clinical classes. The analysis of the statistical significance of the obtained mathematical characteristics in groups by conducting a t-test for two independent samples calculated by the program and the student’s criterion Z-statistics, to conduct a correlation analysis.Results and discussion. Statistical comparative analysis of the RT value as a result of the t-test at the significance level p < 0,05 showed statistically significant differences between С0-С1, С2-С3 and С4-С6 groups with test with (or no) compression cuff. A stable correlation of average strength was observed between the groups in all cases. The differences were not statistically significant between the Norm and C0-C1 groups. The testing hypotheses for adequacy using linear regression methods allowed us to conclude that conducting a photoplethysmographic examination of patients with CVD of different clinical classes as part of the venous reflux test can provide objective information about the effectiveness of the calf muscle - venous pump. A comparative analysis in groups using the criteria RT > 20 sec and 10 < RT < 20 sec showed that there was no correlation between many groups.Conclusion. PPG is not a universal tool for diagnosing disorders of venous hemodynamics in the lower extremities. The value of RT > 20 seconds can be used as a criterion for evaluating the effectiveness of the calf muscle-venous pump, since more than 70% of cases occur in norm and in patients with C0-C1 clinical classes.

Psychophysiological Therapy from a Distance: The Art of Sharing

Psychophysiological Therapy from a Distance: The Art of Sharing

Effect of perioperative penicillin G procaine on bovine castration wound infection rate

Perioperative administration of B-lactam antimicrobials, including penicillin G procaine, is commonly performed at the time of bovine surgical castration despite a paucity of published evidence regarding rate of bovine castration wound infections and efficacy of single-dose perioperative antimicrobial therapy for bovine castration. The best data on frequency of bovine castration complications was generated from a survey of US bovine veterinarians, which reported wound infection, swelling, gait stiffness, and hemorrhage as the most common complications. This same survey identified that a narrow majority of bovine veterinarians routinely utilized perioperative antibiotics, most commonly β-lactams class drugs, including penicillin G procaine. Increasing public demand for antimicrobial stewardship is elevating professional and consumer scrutiny around veterinary antimicrobial use in food animals. In the current climate that increasingly emphasizes judicious use of antimicrobial drugs, it is imperative to base decisions to incorporate antimicrobial prophylaxis into routine protocols on quality evidence. Currently, there is no published data to suggest that perioperative use of PPG reduces scrotal wound or generalized tetanus infection following routine surgical castration of calves. The objective of the study is to establish whether perioperative administration of penicillin G procaine at the time of surgical castration with the Henderson castrating tool decreases the risk of postcastration surgical wound infections.

Intra-Articular Injection of Kartogenin Enhanced Bone Marrow-Derived Mesenchymal Stem Cells in the Treatment of Knee Osteoarthritis

Intra-articular injection of mesenchymal stem cells (MSCs) is an attractive treatment for osteoarthritis (OA) due to their ease of use in clinical settings, excellent safety profile, and remarkable spontaneous cartilage repair. However, significant challenges arise in relation to the control and induction of stem cell differentiation into the desired cartilaginous lineage. Kartogenin (KGN), a hydrophobic small molecule drug, may significantly promote chondrogenic differentiation of MSCs and induce cartilage regeneration in OA. However, low water solubility and poor bioavailability limits its biological application. In this report, we propose a new nano-drug delivery system based on multifunctional nanographene oxide (NGO) to efficiently load KGN molecules noncovalently via π–π stacking and hydrophobic interactions (PPG-KGN), which could quickly enter MSCs. Before intra-articular injection, MSCs are simply mixed and co-incubated with PPG-KGN to acquire KGN enhanced MSCs. This allows the efficient intracellular delivery of KGN, thereby promoting the chondrogenic differentiation potency of the MSCs. We investigated the effect of KGN-enhanced MSCs in the treatment of knee osteoarthritis. An in vitro study showed the PPG could be rapidly uptaken in the first 4 h after incubation, reaching saturation at 12 h, and accumulating in the lysosome and cytoplasm of MSCs. Thus, PPG-KGN could enhance the efficiency of the intracellular delivery of KGN, which showed remarkably high chondrogenic differentiation capacity of the MSCs. When applied to an OA model of cartilage injury in rats, MSCs were preconditioned with PPG-KGN before being injected into the knee joint. It demonstrated the PPG-KGN preconditioned MSCs contribute to protection from joint space narrowing, pathologic mineralization, osteoarthritis development, behavioral assessment of OA-induced pain, and tissue regeneration, as evidenced by radiographic, weight bearing, and histological analysis. Based on these findings, we propose the use of PPG for delivery of KGN to achieve enhanced MSC chondrogenic potential in osteoarthritis treatment.

Automated myocardial infarction identification based on interbeat variability analysis of the photoplethysmographic data

Background and objectiveMyocardial infarction (MI) remains a major cause of mortality around the world for decades. Timely detection followed by instant medical intervention is strongly recommended to minimize MI related death threats. Generally, electrocardiogram (ECG) based automated techniques are preferred to ensure early diagnosis of MI. Recently, Photoplethysmogram (PPG) signal is evolving as a promising diagnostic tool for several cardiac monitoring applications because of its low cost, reliable and easy acquisition technology. However, the use of PPG for MI detection has not been much explored till date. Hence, in the present work, a method for MI detection is proposed based on the use of the PPG signal only. MethodThe pathophysiological alteration due to MI induces a beat-to-beat variation in the PPG beat morphology. Different time-plane parameters from the PPG signal and its derivatives are extracted to represent the individual beat morphologies and their variations are then analyzed as features over the cardiac cycles. By using different feature optimization techniques, finally five features are selected that presents discriminating variability to identify MI. ResultsThe proposed method is evaluated with PPG records collected from 52 hospitalized MI patients and 52 normal subjects. The optimized five feature set, representing the inter beat morphological variations exhibits significant performance along with SVM (linear) classification technique with an average sensitivity, positive predictivity and detection accuracy of 92.70 %, 98.10 %, and 95.40 %, respectively. ConclusionsCompared to other related works, use of PPG signal for MI detection is studied in this research for the first time. The promising result obtained establishes the utility of PPG signal for MI detection with a potential of implementation in the personal healthcare systems.

HRV Assessment Using Finger-tip Photoplethysmography (PulseRate) as Compared to ECG on Healthy Subjects During Different Postures and Fixed Breathing Pattern

Heart Rate Variability (HRV) is a well-known method to assess the human Autonomic Nervous System (ANS) functions. Currently, in the health care information system, HRV properties are very useful to provide medical and other vital signs of the patients. The HRV assessment was derived using the ECG R-R beat interval series, however, using the ECG probes with the electrode’s gel is not convenient for certain people such as who has an allergic symptom and or probes localization in front of the body part that needs certain knowledge how to put it on the correct location. Photoplethysmography (PPG) was considered to be an alternative way to assess HRV using the Peak-to-Peak interval series (PPI). Since previous studies already reported the availability to use PPG to assess HRV instead ECG, this study investigated how the HRV properties using those two methods during different postures with a fixed breathing pattern. Ten subjects participated in this study and we observed the R-R and the Peak-Peak beat interval time series from ECG and PPG respectively during sitting-supine, and standing-supine postures with 3 seconds breathing pattern. The results showed that using PPG to assess HRV still can be used with caution, especially during supine posture that had a deviation (SD) difference between ECG and PPG from the inter-subject analysis (p < 0.05). We concluded that the use of PPG still needs to be carefully considered to assess HRV properties, especially for wearable device and health care information system.

Real-world use of granulocyte colony-stimulating factor in ambulatory breast cancer patients: a cross-sectional study.

To prevent febrile neutropenia (FN), European Organisation for Research and Treatment of Cancer (EORTC) guidelines recommend primary prophylaxis with granulocyte colony-stimulating factors (PPG) for patients at high risk (≥ 20%) of FN. In Belgium, the use of PPG is restricted by specific reimbursement criteria. The impact of these criteria on PPG use and adherence to guidelines is unknown. This multicentre, cross-sectional, observational study aimed to describe PPG use by FN risk category in breast cancer patients who were scheduled to receive myelosuppressive chemotherapy in outpatient clinics in Belgium during a 2-week period between 13 October and 12 December 2014. In total, 490 patients were enrolled. Median age was 57.0years. Based on their chemotherapy regimen, 53.9, 5.1 and 41.0% of patients were at a low, intermediate and high risk of FN, respectively. Overall, 39.8% of patients received PPG (17.0, 12.0 and 73.1% of those receiving low-, intermediate- and high-risk regimens, respectively). In the high-risk category, PPG was used in 89.9% of dose-dense and in 25.0% of classical chemotherapy regimens. PPG use was adherent to EORTC guidelines in 75.3% of patients (30.6% appropriate use, 44.7% appropriate non-use). EORTC guidelines would recommend PPG use in 46.1% of this study population (n = 226), and its use was reimbursable in Belgium in 76.1% of these patients (n = 172), but only 66.4% of them received PPG (n = 150). Both Belgian reimbursement criteria and physician decision-making led to a proportion of patients for whom PPG treatment was recommended but finally not receiving it.

A study on the use of PPG in quantifying circulatory disruptions.

We explore the use of photoplethysmography to monitor and detect changes in arterial and venous circulation for potential use in surgical flap monitoring. The typical disruptions in circulation that are seen in a flap are emulated by occlusion tests conducted in controlled settings. Arterial and venous occlusions are performed on a limited number of subjects, and associated changes in the PPG signals captured at the specific region of interest are analysed. A set of parameters that can be used to distinguish between arterial and venous occlusions are identified and quantified. These parameters may be used to detect thrombosis and differentiate between an arterial and a venous thrombosis in free flaps during postoperative monitoring after reconstructive surgery.

P65 Inhibition of cystathionine gamma-lyase increases endothelium-dependent relaxation of aortic smooth muscles in old rats

Purpose One of the reasons of increasing the risk of cardiovascular diseases during aging is a dysfunction of endothelium. At the same time we can see more and more publications about vascular protection of hydrogen sulfide (H2S). Cystathionine gamma-lyase (CSE) is the main enzyme for H2S synthesis in blood vessels. Methods The segments of aorta from adult and old rats were used. Activation of isolated samples was carried out by phenylephrine (Phe). Acetylcholine (Ach)-mediated vasorelaxation in the aortic vessel were investigated. The activity of CSE was inhibited with propargylglycine (PPG) (incubation 30 min). H2S was determined by N,N-dimethyl-p-phenylenediamine method, NO de novo synthesis – by NOs activity and nitrite determination. Results The experiments on isolated segments of aorta have shown that the effect of Ach endothelium-dependent vasodilator results in less profound relaxation of aortic smooth muscles (SM) in old animals (12.4%) compared to adult ones (66.3%). PPG addition resulted in growing aortic SM relaxation amplitude from 12.4% to 49.5% (p NO 2 - pools. Also increased the activity of cNOS and decreased the activity of iNOS (p Conclusions Therefore, we can state that use of PPG has led to growing production of two powerful vasodilators – H2S and NO and to the restoration of endothelium-dependent aortic SM vasorelaxation in old animals.

Effect of montmorillonite treatment with supercritical CO2 on the morphology and properties of polypropylene nanocomposites

The effects of montmorillonite (MMT) treatment with supercritical carbon dioxide (SC-CO2) on clay morphology and the properties of polypropylene nanocomposites were investigated by wide-angle X-ray diffraction, transmission electron microscopy, scanning electron microscopy, dynamic mechanical analysis, and differential scanning calorimetry. The use of poly(propylene glycol) (PPG) was evaluated. The results showed that the MMT morphology (structure formation, dispersion, and orientation) was affected by treatment with SC-CO2, and the use of PPG, or the use of CO2 in the liquid state. Consequently, different reinforcement measurements were obtained. The relationship between structure and properties was reported.

감성판별을 위한 생체신호기반 특징선택 분류기 설계

감성은 학습, 행동, 의사결정, 상호대화를 포함한 인간의 일상생활에 중요한 요소이다. 본 논문에서는 시스템의 복잡도를 줄이기 위하여 생체신호로부터 최소한의 중요한 특징만을 추출하여 사용하는 감성 분류기를 설계하고자 한다. 생체신호는 맥파,피부온도, 피부전도도, 뇌파신호(전두엽, 두정엽)를 사용하였으며, 4가지 감정(보통, 슬픔, 공포, 행복)은 영화 관람을 통하여 유도하였다. 측정한 생체신호로부터 추출한 24개의 특징으로부터 최적의 특징 집합의 결정은 서포트벡터머신 기반 적합도 함수를 사용하는 유전알고리즘을 적용하였다. 최적의 4감정 분류 정확도는 96.4%이었으며, 서포트벡터머신만을 사용하였을 경우보다 17% 높았다. 선택된 최소에러 특징은 맥파 심박변이도의 평균, NN50, 맥파 유도 맥파 전달 시간의 평균, 피부전도도의 평균과 두정엽 뇌파의 δ, β 주파수 대역에너지였다. 실험을 통하여 두정엽 뇌파, 맥파, 피부전도도의 조합이 고정밀 감정 장비에 적합하였으며, 79% 성능을 보인 맥파와 피부전도도의 조합이 간단한 감성장비에 적절하게 적용할 수 있다.

Inhibitory effects of purpurogallin on the endothelial protein C receptor shedding in vitro and in vivo

Endothelial cell protein C receptor (EPCR) plays important roles in the regulation of blood coagulation and inflammation. Activity of EPCR is markedly changed by ectodomain cleavage and released as soluble protein (sEPCR). EPCR can be shed from the cell surface, and this is mediated by tumor necrosis factor-α converting enzyme (TACE). Purpurogallin (PPG) plays an important role in inhibiting glutathione S-transferase and xanthine oxidase as well as effective in the cell protection of several cell types. Here, we investigated the effects of PPG on phorbol-12-myristate 13-acetate (PMA), tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and on cecal ligation and puncture (CLP)-mediated EPCR shedding and underlying mechanisms. Human umbilical vein endothelial cells pretreated with PPG (0, 5, 10, 20 or 50 μg/mL) for 6 h and exposed to PMA (1 μM) for 1 h, and CLP-operated mice were administrated with PPG. Data showed that treatment with PPG resulted in potent inhibition of PMA, TNF-α, IL-1β, and CLP-induced EPCR shedding by suppression of TACE expression. In addition, PPG reduced PMA-stimulated phosphorylation of p38, extracellular regulated kinases 1/2, and c-Jun N-terminal kinase. These results suggest the potential for use of PPG as an anti-sEPCR shedding reagent against PMA and CLP-mediated EPCR shedding.